Plenoptic cameras (also known as lightfield cameras) have recently become commercially available for industrial and consumer applications. Plenoptic cameras capture the distribution of light rays in space based upon a four dimensional plenoptic function. The four dimensional information captured by a plenoptic camera may be utilized, for example, in rendering 3D imagery, providing computer vision functionality, and allowing photographers to set the focus in a scene after the image is captured. Both spatial and Fourier slice techniques have been utilized in processing and rendering images captured by conventional plenoptic cameras, however, regardless of the technique(s) used, conventional plenoptic cameras render 2D images that are too small to satisfy the demands and expectations of modern imaging and photography applications.
The focused plenoptic camera is a recently developed alternative to the conventional plenoptic camera. The focused plenoptic camera uses a microlens array as an imaging system focused on the focal plane of the main camera lens. The focused plenoptic camera captures lightfields with a different tradeoff between spatial and angular information than with the conventional plenoptic camera, and can capture lightfields with significantly higher spatial resolution than conventional plenoptic cameras. As a result, spatial resolution of focused plenoptic cameras may be provided at a level comparable to that of non-plenoptic digital cameras.
Existing plenoptic image processing systems and processes suffer from a number of disadvantages and shortcomings. Existing spatial transform techniques for images captured by either a conventional plenoptic camera or a focused plenoptic camera have higher computational complexity than Fourier techniques when many rendered images are being generated. More specifically, existing spatial transform techniques have an O(n^4) time cost per image, while the techniques disclosed herein may have an O(n^4 log n) time cost up front but only an O(n^2) time cost required per image. Existing filtering techniques for noise removal in plenoptic images are quite complex because they are based on the original image rather than its Fourier transform. In contrast, the systems and processes disclosed herein make filtering the image much easier both before and after rendering. Existing Fourier techniques are specific to images from a conventional plenoptic camera and even in that application suffer from limitations and drawbacks including limited data capture and limited image resolution. There remains a significant unmet need for the unique apparatuses, methods, systems and techniques disclosed herein.